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HR Department
Ai Data AI technology AI tools Cyber Security Data Services Data Technology GenAI HR Department

How GenAI Is Revolutionizing HR Analytics for CHROs and Business Leaders

 

Generative AI (GenAI) is redefining how HR leaders interact with data, removing the steep learning curve traditionally associated with people analytics tools. When faced with a spike in hourly employee turnover, Sameer Raut, Vice President of HRIS at Sunstate Equipment, didn’t need to build a custom report or consult data scientists. Instead, he typed a plain-language query into a GenAI-powered chatbot: 

“What are the top reasons for hourly employee terminations in the past 12 months?” Within seconds, he had his answer. This shift in how HR professionals access data marks a significant evolution in workforce analytics. Tools powered by large language models (LLMs) are now integrated into leading analytics platforms such as Visier, Microsoft Power BI, Tableau, Qlik, and Sisense. These platforms are leveraging GenAI to interpret natural language questions and deliver real-time, actionable insights without requiring technical expertise. 

One of the major advantages of GenAI is its ability to unify fragmented HR data sources. It streamlines data cleansing, ensures consistency, and improves the accuracy of workforce metrics like headcount growth, recruitment gaps, and attrition trends. As Raut notes, tools like Visier’s GenAI assistant “Vee” allow him to make quick decisions during meetings, helping HR become more responsive and strategic. This evolution is particularly valuable in a landscape where 39% of HR leaders cite limited analytics expertise as their biggest challenge, according to a 2023 Aptitude Research study. 

GenAI removes this barrier by enabling intuitive data exploration across familiar platforms like Slack and Microsoft Teams. Frontline managers who may never open a BI dashboard can now access performance metrics and workforce trends instantly. Experts believe this transformation is just beginning. While some analytics platforms are still improving their natural language processing capabilities, others are leading with more advanced and user-friendly GenAI chatbots. 

These tools can even create automated visualizations and summaries tailored to executive audiences, enabling CHROs to tell compelling data stories during high-level meetings. However, this transformation doesn’t come without risk. Data privacy remains a top concern, especially as GenAI tools engage with sensitive workforce data. HR leaders must ensure that platforms offer strict entitlement management and avoid training AI models on private customer data. Providers like Visier mitigate these risks by training their models solely on anonymized queries rather than real-world employee information. 

As GenAI continues to evolve, it’s clear that its role in HR will only expand. From democratizing access to HR data to enhancing real-time decision-making and storytelling, this technology is becoming indispensable for organizations looking to stay agile and informed.
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Twitter
Ai Data AI Models Cyber Security Data protection data security DPC EDPB EU Personal Data Twitter

Irish Data Protection Commission Halts AI Data Practices at X

 

The Irish Data Protection Commission (DPC) recently took a decisive step against the tech giant X, resulting in the immediate suspension of its use of personal data from European Union (EU) and European Economic Area (EEA) users to train its AI model, “Grok.” This marks a significant victory for data privacy, as it is the first time the DPC has taken such substantial action under its powers granted by the Data Protection Act of 2018. 

The DPC initially raised concerns that X’s data practices posed a considerable risk to individuals’ fundamental rights and freedoms. The use of publicly available posts to train the AI model was viewed as an unauthorized collection of sensitive personal data without explicit consent. This intervention highlights the tension between technological innovation and the necessity of safeguarding individual privacy. 

Following the DPC’s intervention, X agreed to cease its current data processing activities and commit to adhering to stricter privacy guidelines. Although the company did not acknowledge any wrongdoing, this outcome sends a strong message to other tech firms about the importance of prioritizing data privacy when developing AI technologies. The immediate halt of Grok AI’s training on data from 60 million European users came in response to mounting regulatory pressure across Europe, with at least nine GDPR complaints filed during its short stint from May 7 to August 1. 

After the suspension, Dr. Des Hogan, Chairperson of the Irish DPC, emphasized that the regulator would continue working with its EU/EEA peers to ensure compliance with GDPR standards, affirming the DPC’s commitment to safeguarding citizens’ rights. The DPC’s decision has broader implications beyond its immediate impact on X. As AI technology rapidly evolves, questions about data ethics and transparency are increasingly urgent. This decision serves as a prompt for a necessary dialogue on the responsible use of personal data in AI development.  

To further address these issues, the DPC has requested an opinion from the European Data Protection Board (EDPB) regarding the legal basis for processing personal data in AI models, the extent of data collection permitted, and the safeguards needed to protect individual rights. This guidance is anticipated to set clearer standards for the responsible use of data in AI technologies. The DPC’s actions represent a significant step in regulating AI development, aiming to ensure that these powerful technologies are deployed ethically and responsibly. By setting a precedent for data privacy in AI, the DPC is helping shape a future where innovation and individual rights coexist harmoniously.
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Financial Security
Ai Data AI technology Cortex-M Cyber Security Cyberattack data security Financial Security

Snowflake Faces Declining Growth Amid Cybersecurity Concerns and AI Expansion

 

Snowflake Inc. recently faced a challenging earnings period marked by slowing growth and concerns following multiple cyberattacks. Despite being an AI data company with innovative technology, these events have impacted investor confidence, causing the stock price to retest recent lows. The company’s latest financial results reflect a continuing trend of decelerating growth, which is compounded by a valuation that assumes far higher growth rates than currently achieved.  

Snowflake’s sales growth has slowed considerably, with its FQ2 revenue growing by just under 29%, down from nearly 33% in the previous quarter. Projections for FQ3 suggest an even sharper decline, with product revenue growth forecasted to rise by only 22% year-over-year. The slowdown in revenue is significant, with growth rates expected to dip to as low as 20% in FQ4. In past quarters, Snowflake experienced higher sequential growth on a much smaller base, indicating that the company’s growth challenges are becoming more pronounced as it scales. The deceleration in sales has not been mitigated by the company’s focus on AI. During the earnings call, Snowflake highlighted the adoption of AI technologies among its 2,500 customers. 

However, these new product features, such as those centered around AI products like Cortex, are not expected to materially impact revenues in the near term. Snowflake’s guidance for FY 2025 does not factor in any significant contributions from these AI initiatives, further dampening expectations for a quick turnaround. Snowflake’s recent performance is further complicated by lingering cybersecurity issues. The company faced a series of cyberattacks where customer data stored on their platforms was compromised, partly due to inadequate sign-on controls by customers. Additionally, the recent CrowdStrike (CRWD) cybersecurity incident has only added to investor concerns about the company’s data security posture. 

Despite the concerns, Snowflake points to growth in remaining performance obligations (RPOs), with commitments reaching $5.2 billion, a 48% increase. Yet, management admits that RPOs may not be the best leading indicator for growth, given that product revenue is declining. The company also contends with multiple top customers operating on flexible, month-to-month contracts, which creates uncertainty in long-term revenue projections. Snowflake remains priced for perfection, trading at 12 times its FY25 revenue target of $3.5 billion, with a fully diluted market cap of $41.4 billion. However, the stock price has already fallen nearly 50% this year, and non-GAAP gross margins are slim, sitting at just 5% in the most recent quarter. 

While Snowflake generates significant free cash flow due to upfront customer payments, it also carries future obligations, further straining its financial outlook. The key takeaway for investors is that while Snowflake continues to innovate in AI and data management, it faces substantial headwinds due to slowing growth, cybersecurity concerns, and a valuation that does not reflect current market realities. Given these factors, potential investors might be wise to stay on the sidelines until there is clearer evidence of a turnaround in the company’s growth trajectory.
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Technology
AI Ai Data Artificial Intelligence Artificial intelligence Education Data data security Education Safety Security. Data Technology

Optimizing Education: Unleashing the Potential of Artificial Intelligence in the Classroom

 

The incorporation of Artificial Intelligence (AI) into educational settings holds the promise of transforming both the learning experience for students and the teaching methods employed by educators. AI algorithms, when integrated into the classroom, have the capability to offer personalized feedback and recommendations, enhancing the overall efficacy and engagement in learning. 

Despite these potential advantages, educators encounter various challenges in integrating AI into the curriculum. This article explores the benefits, challenges, and best practices associated with the inclusion of AI in education, emphasizing the ongoing need for research and development to fully harness its potential.

Artificial Intelligence is progressively becoming an integral part of our daily lives, with the potential to revolutionize work, communication, and learning. In the educational realm, AI stands to provide students with personalized and engaging learning experiences, aiding teachers in addressing individual student needs more effectively. 

However, along with these benefits, educators face challenges such as the requirement for technical expertise, limited resources, and ethical considerations.

Benefits of Incorporating AI into the Classroom

One significant advantage of integrating AI into classrooms is the ability to tailor learning experiences to individual students. AI algorithms analyze student data, adapting to their learning styles and offering feedback and recommendations customized to their needs. This personalized approach can enhance student engagement, motivation, and ultimately contribute to improved academic performance. 

Additionally, incorporating AI into the curriculum provides an opportunity to deepen students' understanding of this rapidly-evolving technology, fostering a critical perspective and preparing them for the challenges and opportunities of the digital age. Moreover, exposure to AI tools and applications helps students develop crucial 21st-century skills such as problem-solving, critical thinking, and collaboration.

Challenges of Incorporating AI into the Classroom

While the advantages of incorporating AI into education are evident, educators face significant challenges. The foremost obstacle is the need for technical expertise, as teachers unfamiliar with AI may struggle to seamlessly integrate it into their teaching practices. 

Addressing this challenge requires adequate support and training. Another hurdle is the cost associated with AI tools and applications, posing resource constraints for many educational institutions. Additionally, ethical concerns regarding privacy, security, and the impact on the job market require careful consideration to ensure responsible implementation.

To champion the cause of AI, one must adopt a critical stance and acknowledge the potential for misuse or mishandling. It is crucial to identify these potential pitfalls and initiate discussions on effective mitigation strategies.

Instances of students leveraging generative AI services, such as ChatGPT, for academic dishonesty have surfaced. Relying solely on algorithms and AI for the learning journey is not the objective.

The emphasis should be on enhancing, not overshadowing, the learning experience. While tools like ChatGPT can be potent aids, their effectiveness depends on how thoughtfully they are integrated. Educating both students and teachers on the strategic use of AI tools is essential. For instance, rather than allowing unrestricted use, schools can integrate ChatGPT into project-based learning, fostering a research-oriented mindset. Students can employ ChatGPT as a co-pilot, supplementing their own hypotheses and interpretations, thereby making classroom learning engaging and enriching.

To effectively integrate AI into teaching practices, several best practices are recommended:

1. Partner with a Reliable AI Provider:Collaborate with trustworthy AI partners, such as technology companies, local universities, or non-profit organizations specializing in AI education. These partners can offer support, training, and guidance for seamless integration.

2. Start Small:Begin by implementing AI in specific areas rather than attempting a comprehensive curriculum overhaul. This incremental approach allows teachers to gain experience, build confidence, and refine their teaching methods gradually.

3. Foster Ethical and Critical Thinking:Encourage students to think critically about the ethical implications of AI and its societal impact. This promotes responsible and informed digital citizenship, empowering students to navigate the challenges and opportunities presented by AI.

Overall, the integration of Artificial Intelligence into education presents a unique opportunity for both educators and students. 

While AI holds the potential to offer personalized learning experiences and develop essential 21st-century skills, its incorporation requires careful consideration of challenges and adherence to best practices. Ongoing research and development are essential to fully unlock the transformative potential of AI in education.
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